Chapter 18. Discriminant and Cluster Analysis
Overview
Both discriminant analysis and cluster analysis classify observations into groups. The difference is that discriminant analysis has actual groups to predict, whereas cluster analysis forms groups of points that are close together.
Discriminant Analysis
Discriminant analysis is appropriate for situations where you want to classify a categorical variable based on values of continuous variables. For example, you may be interested in the voting preferences (Democrat, Republican, or Other) of people of various ages and income levels. Or, you may want to classify animals into different species based on physical measurements of the animal.
There is a strong similarity between discriminant analysis and ...
Get JMP® Start Statistics: A Guide to Statistics and Data Analysis Using JMP®, 4th Edition now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
